Spectral Clustering and Vantage Point Indexing for Efficient Data Retrieval

Data mining is an essential process for identifying the patterns in large datasets through machine learning techniques and database systems. Clustering of high dimensional data is becoming very challenging process due to curse of dimensionality. In addition, space complexity and data retrieval performance was not improved. In order to overcome the limitation, Spectral Clustering Based VP Tree Indexing Technique is introduced. The technique clusters and indexes the densely populated high dimensional data points for effective data retrieval based on user query. A Normalized Spectral Clustering Algorithm is used to group similar high dimensional data points. After that, Vantage Point Tree is constructed for indexing the clustered data points with minimum space complexity. At last, indexed data gets retrieved based on user query using Vantage Point Tree based Data Retrieval Algorithm.  This in turn helps to improve true positive rate with minimum retrieval time. The performance is measured in terms of space complexity, true positive rate and data retrieval time with El Nino weather data sets from UCI Machine Learning Repository. An experimental result shows that the proposed technique is able to reduce the space complexity by 33% and also reduces the data retrieval time by 24% when compared to state-of-the-art-works

A Study on the Performances of Representation Strategies Handled For Text Categorization

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Performance of Lung Carcinoma in Classification Neural Network with Pre Processing Using WEGA

Data pre processing ease the mining procedure by removing the insignificant information and errors that may arise while entering the data manually. The data collection method is not strict so there accompanies missing and incorrect values, irrelevant variables, data with out of range etc. These have significant impact and minimize the accuracy of the mining process. Generally accuracy in the case of medical research must reach to the extent. There are many factors affect the analysis on the given task. The precise representation and quality of the dataset is vital. If there exists more irrelevant and redundant information the meaningful discovery of knowledge is a big question. Pre processing is a prominent way for the data preparation and thus it the earlier stage in mining. It includes many variant procedures according to the problem of the set. The output is taken as the direct training set for further research. This research analyse the Lung cancer dataset with fifteen attributes by applying pre processing method attribute evaluation. This method reduce the dimensionality, file size and time taken for the analysis by considering only on the most relevant variables. The work is carried in the WEKA tool as it has enormous procedures for data preparation. The performance before and after pre processing is discussed with suitable metrics

Acetabular fractures –Clinical outcomes of surgical management

Introduction : The fractures of acetabulum concern 2% of fractures and it is difficult to be diagnosed and treated.Improvements in automobile safety, pre-hospital care, resuscitation and transport as well as standardized protocols for treatment have all contributed to improved survival after these devastating injuries Materials and methods : The operative treatment of acetabular fractures was performed in Vinayaka Mission Kirupananda Variyar Medical College and Hospital from July 2010 to July 2019. 32 patients had an open reduction and internal fixation of an acetabular fracture. 25 were males and 7 were females, with an age ranging from 28 to 62 years (average: 36.7 years). The mechanism of injury was a motor vehicle accident in most cases (85%). The fractures were classified with Judet-Letournel classification. The patients were operated upon within 1-8 days (average: 4 days). The Kocher-Langenbeck surgical approach was used in 22 cases and ilioinguinal approach in 10 patients. Osteosynthesis was achieved with either lag screws alone or with a combination of lag screws and a buttress plate. Follow-up ranged from 6 months - 9 years (average: 3.8 years). Results: Clinical evaluation according to the D' Aubigne-Postel scoring system gave 23 excellent (71.9%), 6 good (18.8%), 2 fair (6.3%) and 1 poor (3.1%) results. Early postoperative complications included 1 case of unexplained bleeding through drain tube for 8 days and superficial wound infection in another 3 patients. Conclusion : Operative treatment of acetabular fractures although demanding, bears very good results

SKILL ACQUISITION FOR ENHANCING EMPLOYABILITY THROUGH MULTIPLE LEARNING EXPERIENCE INSTRUCTIONAL STRATEGY (MLEIS) – TOWARDS ENSURING INCLUSIVE AND EQUITABLE TECHNOLOGY EDUCATION

Matching skills to jobs has long been one of the important goals of education. The National Employability Report (2016) has highlighted the fact that engineering graduates do not fulfill the basic criteria of employability. It has been reported the current strategies do not address multiple modes and levels of numeracy, programming, computer literacy, algorithm and programming. It was revealed that students find certain subjects quite difficult and the objective based achievement test revealed failure to realize learning objectives and learning outcomes. Theory based instructional strategies and lecture mode of instructional delivery has been found to be not suited for engineering education [1]. In this study, the effectiveness of a Multiple Learning Experience based Instructional strategy (MLEIS) is explored. MLEIS is based on theories of learning, instruction design, learning styles and techno pedagogies. MLEIS envisages a skill based curricular strategy which addresses diversity, inclusiveness focusing on aspects like skill development, skill acquisition, professional competency and subject comprehension.  Article visualizations

EVALUATION OF IN VITRO ANTICANCER POTENTIAL OF ETHANOLIC EXTRACT AND ITS DIFFERENT FRACTIONS OF CAESALPINIA BONDUC (L) ROXB SEEDS

Objective: The present study aims to evaluate the anticancer potential of ethanolic extract and its different fractions of Caesalpinia bonduc seeds against Ehrlich Ascites Carcinoma (EAC) cell lines. Methods: Ethanolic extract and its fractions were subjected to preliminary phytochemical screening and anticancer activity by using in vitro anticancer assay. Chemical constituents of petroleum ether fraction of C. bonduc seeds were identified by using GC-MS and the active compounds were subjected to in silico studies. Results: In vitro anticancer assay showed that the petroleum ether fraction of ethanolic extract of Caesalpinia bonduc seeds has potential anticancer activity. Conclusions: Petroleum ether fraction of ethanolic extract of Caesalpinia bonduc seeds has significant anticancer activity. Further in-depth studies, could result in the development of a good anticancer agent from the seeds of Caesalpinia bonduc

Molecular Approaches for Insect Pest Management in Rice

AbstractThis chapter focuses on the progress made in using molecular tools in understanding resistance in rice to insect pests and breeding rice for multiple and durable insect resistance. Currently, molecular markers are being extensively used to tag, map, introgress, and clone plant resistance genes against gall midge, planthoppers, and leafhoppers. Studies on cloned insect resistance genes are leading to a better understanding of plant defense against insect pests under different feeding guilds. While marker-assisted breeding is successfully tackling problems in durable and multiple pest resistance in rice, genomics of plants and insects has identified RNAi-based gene silencing as an alternative approach for conferring insect resistance. The use of these techniques in rice is in the developmental stage, with the main focus on brown planthopper and yellow stem borer. CRISPR-based genome editing techniques for pest control in plants has just begun. Insect susceptibility genes (negative regulators of resistance genes) in plants are apt targets for this approach while gene drive in insect populations, as a tool to study rice-pest interactions, is another concept being tested. Transformation of crop plants with diverse insecticidal genes is a proven technology with potential for commercial success. Despite advances in the development and testing of transgenic rice for insect resistance, no insect-resistant rice cultivar is now being commercially cultivated. An array of molecular tools is being used to study insect-rice interactions at transcriptome, proteome, metabolome, mitogenome, and metagenome levels, especially with reference to BPH and gall midge, and such studies are uncovering new approaches for insect pest management and for understanding population genetics and phylogeography of rice pests. Thus, it is evident that the new knowledge being gained through these studies has provided us with new tools and information for facing future challenges. However, what is also evident is that our attempts to manage rice pests cannot be a one-time effort but must be a continuing one

Simulation of Cantilever Based Sensors for Smart Textile Applications

Abstract: Smart fabrics enable the integration of electronics into fabric. They can serve as a suitable sensor, providing around the clock assistance for the real time monitoring of health parameters. In this work, we aim to develop a free standing piezoelectric cantilever sensor integrated over the conventional fabric to improve their functionality. These smart sensors facilitate the conversion of physiological parameters or movement into electrical signals that can be further processed and evaluated. Here, a basic design of such a sensor is simulated using COMSOL Multiphysics 4.3b

Progress and prospects in harnessing wild relatives for genetic enhancement of salt tolerance in rice

Salt stress is the second most devastating abiotic stress after drought and limits rice production globally. Genetic enhancement of salinity tolerance is a promising and cost-effective approach to achieve yield gains in salt-affected areas. Breeding for salinity tolerance is challenging because of the genetic complexity of the response of rice plants to salt stress, as it is governed by minor genes with low heritability and high G × E interactions. The involvement of numerous physiological and biochemical factors further complicates this complexity. The intensive selection and breeding efforts targeted towards the improvement of yield in the green-revolution era inadvertently resulted in the gradual disappearance of the loci governing salinity tolerance and a significant reduction in genetic variability among cultivars. The limited utilization of genetic resources and narrow genetic base of improved cultivars have resulted in a plateau in response to salinity tolerance in modern cultivars. Wild species are an excellent genetic resource for broadening the genetic base of domesticated rice. Exploiting novel genes of underutilized wild rice relatives to restore salinity tolerance loci eliminated during domestication can result in significant genetic gain in rice cultivars. Wild species of rice, Oryza rufipogon and Oryza nivara, have been harnessed in the development of a few improved rice varieties like Jarava and Chinsura Nona 2. Furthermore, increased access to sequence information and enhanced knowledge about the genomics of salinity tolerance in wild relatives has provided an opportunity for the deployment of wild rice accessions in breeding programs, while overcoming the cross-incompatibility and linkage drag barriers witnessed in wild hybridization. Pre-breeding is another avenue for building material that are ready for utilization in breeding programs. Efforts should be directed towards systematic collection, evaluation, characterization, and deciphering salt tolerance mechanisms in wild rice introgression lines and deploying untapped novel loci to improve salinity tolerance in rice cultivars. This review highlights the potential of wild relatives of Oryza to enhance tolerance to salinity, track the progress of work, and provide a perspective for future research